Business modelling for a digital compliance platform: taking stock and looking forward : (D3.2.1 Desk study and interviews)

This study consists of a desk study on business models related to Ag data platforms and stakeholder consultation through interviews and stakeholder workshops (information on the interviews can be found in the Section References). An Ag data platform is interpreted as an IT-based interorganisational arrangement dealing with the collection, storage, exchange and use of Ag data. The scope of the desk study is limited to Ag data platforms with publicly available information on their key features. 8 | Wageningen Economic Research Report 2017-014 The objective of this study is to examine main types of business models that are used for developing Ag data platforms in agrifood chains and identify viable options that can be used for future development of the compliance platform envisaged by FarmDigital. More specifically, the research intends to provide answers to the following questions: What types of business models are being used for Ag data platforms? What features characterise the current landscape of Ag data platforms? What are the analogs and antilogs of the compliance platform envisaged by FarmDigital? What are the challenges and enabling options for future development of a compliance platform

Advancing food, nutrition, and health research in Europe by connecting and building research infrastructures in a DISH-RI: Results of the EuroDISH project

Background: Research infrastructures (RIs) are essential to advance research on the relationship between food, nutrition, and health. RIs will facilitate innovation and allow insights at the systems level which are required to design (public health) strategies that will address societal challenges more effectively. Approach: In the EuroDISH project we mapped existing RIs in the food and health area in Europe, identified outstanding needs, and synthesised this into a conceptual design of a pan-European DISH-RI. The DISH model was used to describe and structure the research area: Determinants of food choice, Intake of foods and nutrients, Status and functional markers of nutritional health, and Health and disease risk. Key findings: The need to develop RIs in the food and health domain clearly emerged from the EuroDISH project. It showed the necessity for a unique interdisciplinary and multi-stakeholder RI that overarches the research domains. A DISH-RI should bring services to the research community that facilitate network and community building and provide access to standardised, interoperable, and innovative data and tools. It should fulfil the scientific needs to connect within and between research domains and make use of current initiatives. Added value can also be created by providing services to policy makers and industry, unlocking data and enabling valorisation of research insights in practice through public-private partnerships. The governance of these services (e.g. ownership) and the centralised and distributed activities of the RI itself (e.g. flexibility, innovation) needs to be organised and aligned with the different interests of public and private partners

Adviezen voor een actieve rol van Nederland in Europees kennis- en innovatiebeleid voor transitie naar duurzame voedselsystemen

The key question in this study is: Where and how can LNV influence European knowledge & innovation policy for the transition of the food system? In addition to the regular policy channels for LNV’s input into European decision-making, LNV could seek to join the defining working groups that are establishing frameworks for the Dutch food system transition and build on the efforts of key figures and key networks in the knowledge domain. The study used an exploratory analysis of spheres of influence based on secondary sources, five interviews and a workshop. The study provides recommendations for LNV’s knowledge and innovation policy

Ethics of smart farming : Current questions and directions for responsible innovation towards the future

Sensors, drones, weather satellites and robots are examples of technologies that make farming ‘smart’. In this article we present the results of our review of the literature that concerns the ethical challenges that smart farming raises. Our reading suggests that current ethical discussion about smart farming circles around three themes: (1) data ownership and access, (2) distribution of power and (3) impacts on human life and society. Discussions that fall under these themes have however not yet reached a satisfying conclusion, as there seem to be different ideas at work in the background regarding the purpose and function of digital farms in society. The pros and cons of these rivalling ideas are rarely foregrounded in the discussion. We suggest that future research should focus first on the content of these goals, especially on the content of societal and commercial goals and whether and how they can be combined in differing contexts. This will offer a lead to think about what data ought to be shared with whom, to set preconditions for trust between stakeholders and –eventually- develop appropriate guidelines and codes of conduct for future farming digitalization trajectories.</p

Ethics of smart farming : Current questions and directions for responsible innovation towards the future

Sensors, drones, weather satellites and robots are examples of technologies that make farming ‘smart’. In this article we present the results of our review of the literature that concerns the ethical challenges that smart farming raises. Our reading suggests that current ethical discussion about smart farming circles around three themes: (1) data ownership and access, (2) distribution of power and (3) impacts on human life and society. Discussions that fall under these themes have however not yet reached a satisfying conclusion, as there seem to be different ideas at work in the background regarding the purpose and function of digital farms in society. The pros and cons of these rivalling ideas are rarely foregrounded in the discussion. We suggest that future research should focus first on the content of these goals, especially on the content of societal and commercial goals and whether and how they can be combined in differing contexts. This will offer a lead to think about what data ought to be shared with whom, to set preconditions for trust between stakeholders and –eventually- develop appropriate guidelines and codes of conduct for future farming digitalization trajectories.</p